Improve header and variable naming in write_smoother_results.m
Johannes Pfeifer
parent
8b21443284
commit
b749a3ce75
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@ -8,28 +8,50 @@ function [oo_, yf]=write_smoother_results(M_,oo_,options_,bayestopt_,dataset_,da
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% options_ [structure] storing the options
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% bayestopt_ [structure] storing information about priors
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% dataset_ [structure] storing the dataset
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% atT [double] (m*T) matrix, smoothed endogenous variables (a_{t|T})
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% atT [double] (m*T) matrix, smoothed endogenous variables (a_{t|T}) (decision-rule order)
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% innov [double] (r*T) matrix, smoothed structural shocks (r>n is the umber of shocks).
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% measurement_error [double] (n*T) matrix, smoothed measurement errors.
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% updated_variables [double] (m*T) matrix, updated (endogenous) variables (a_{t|T})
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% ys [double] (m*1) vector specifying the steady state level of each endogenous variable.
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% updated_variables [double] (m*T) matrix, updated (endogenous) variables (a_{t|t}) (decision-rule order)
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% ys [double] (m*1) vector specifying the steady state
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% level of each endogenous variable (declaration order)
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% trend_coeff [double] (n*1) vector, parameters specifying the slope of the trend associated to each observed variable.
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% aK [double] (K,n,T+K) array, k (k=1,...,K) steps ahead filtered (endogenous) variables.
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% P [3D array] of one-step ahead forecast error variance
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% matrices
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% PK [4D array] of k-step ahead forecast error variance
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% matrices (meaningless for periods 1:d)
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% decomp
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% aK [double] (K,n,T+K) array, k (k=1,...,K) steps ahead
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% filtered (endogenous) variables (decision-rule order)
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% P [3D array] (m*m*(T+1)) array of one-step ahead forecast error variance
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% matrices (decision-rule order)
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% PK [4D array] (K*m*m*(T+K)) 4D array of k-step ahead forecast error variance
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% matrices (meaningless for periods 1:d) (decision-rule order)
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% decomp [4D array] (K*m*r*(T+K)) 4D array of shock decomposition of k-step ahead
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% filtered variables (decision-rule order)
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% Trend [double] [nvarobs*T] matrix of trends in observables
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%
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% Outputs:
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% oo_ [structure] storing the results
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% yf [double] (nvarobs*T) matrix storing the smoothed observed variables
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% oo_ [structure] storing the results:
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% oo_.Smoother.SteadyState: Steady states (declaration order)
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% oo_.Smoother.TrendCoeffs: trend coefficients (order of options_.varobs)
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% oo_.Smoother.Variance: one-step ahead forecast error variance (declaration order)
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% oo_.Smoother.Constant: structure storing the constant term of the smoother
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% oo_.Smoother.Trend: structure storing the trend term of the smoother
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% oo_.FilteredVariablesKStepAhead: k-step ahead forecast error variance matrices (decision-rule order)
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% oo_.FilteredVariablesShockDecomposition: shock decomposition of k-step ahead filtered variables (decision-rule order)
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% oo_.FilteredVariables: structure storing the filtered variables
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% oo_.UpdatedVariables: structure storing the updated variables
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% oo_.SmoothedShocks: structure storing the smoothed shocks
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% oo_.SmoothedMeasurementErrors: structure storing the smoothed measurement errors
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% yf [double] (nvarobs*T) matrix storing the smoothed observed variables (order of options_.varobs)
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%
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% Notes: first all smoothed variables are saved without trend and constant.
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% Notes:
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% m: number of endogenous variables (M_.endo_nbr)
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% T: number of Time periods (options_.nobs)
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% r: number of strucural shocks (M_.exo_nbr)
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% n: number of observables (length(options_.varobs))
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% K: maximum forecast horizon (max(options_.nk))
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%
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% First all smoothed variables are saved without trend and constant.
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% Then trend and constant are added for the observed variables.
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%
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% Copyright (C) 2014 Dynare Team
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% Copyright (C) 2014-2016 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -88,35 +110,35 @@ if options_.filter_covariance
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oo_.Smoother.Variance = P;
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end
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%get indicees of smoothed variables
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i_endo = bayestopt_.smoother_saved_var_list;
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%get indices of smoothed variables
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i_endo_in_dr = bayestopt_.smoother_saved_var_list;
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if ~isempty(options_.nk) && options_.nk ~= 0 && (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape> 0) && options_.load_mh_file)))
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%write deviations from steady state, add constant for observables later
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oo_.FilteredVariablesKStepAhead = aK(options_.filter_step_ahead,i_endo,:);
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oo_.FilteredVariablesKStepAhead = aK(options_.filter_step_ahead,i_endo_in_dr,:);
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if ~isempty(PK) %get K-step ahead variances
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oo_.FilteredVariablesKStepAheadVariances = ...
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PK(options_.filter_step_ahead,i_endo,i_endo,:);
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PK(options_.filter_step_ahead,i_endo_in_dr,i_endo_in_dr,:);
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end
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if ~isempty(decomp) %get decomposition
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oo_.FilteredVariablesShockDecomposition = ...
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decomp(options_.filter_step_ahead,i_endo,:,:);
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decomp(options_.filter_step_ahead,i_endo_in_dr,:,:);
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end
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end
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for i=bayestopt_.smoother_saved_var_list'
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i1 = oo_.dr.order_var(bayestopt_.smoother_var_list(i)); %get indices of smoothed variables in name vector
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for dr_index=bayestopt_.smoother_saved_var_list'
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i1 = oo_.dr.order_var(bayestopt_.smoother_var_list(dr_index)); %get indices of smoothed variables in name vector
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%% Compute constant
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if options_.loglinear == 1 %logged steady state must be used
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constant_current_variable=repmat(log(ys(i1)),gend,1);
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elseif options_.loglinear == 0 %unlogged steady state must be used
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constant_current_variable=repmat((ys(i1)),gend,1);
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end
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oo_.SmoothedVariables.(deblank(M_.endo_names(i1,:)))=atT(i,:)'+constant_current_variable;
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oo_.SmoothedVariables.(deblank(M_.endo_names(i1,:)))=atT(dr_index,:)'+constant_current_variable;
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if ~isempty(options_.nk) && options_.nk > 0 && ~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape> 0) && options_.load_mh_file))
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oo_.FilteredVariables.(deblank(M_.endo_names(i1,:)))=squeeze(aK(1,i,2:end-(options_.nk-1)));
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oo_.FilteredVariables.(deblank(M_.endo_names(i1,:)))=squeeze(aK(1,dr_index,2:end-(options_.nk-1)));
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end
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oo_.UpdatedVariables.(deblank(M_.endo_names(i1,:)))=updated_variables(i,:)'+constant_current_variable;
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oo_.UpdatedVariables.(deblank(M_.endo_names(i1,:)))=updated_variables(dr_index,:)'+constant_current_variable;
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end
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%% Add trend and constant for observed variables
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@ -141,8 +163,8 @@ for pos_iter=1:length(bayestopt_.mf)
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end
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%% get smoothed shocks
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for i=1:M_.exo_nbr
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oo_.SmoothedShocks.(deblank(M_.exo_names(i,:)))=innov(i,:)';
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for exo_iter=1:M_.exo_nbr
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oo_.SmoothedShocks.(deblank(M_.exo_names(exo_iter,:)))=innov(exo_iter,:)';
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end
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%% Smoothed measurement errors
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